Convergence criterion for MBIR based on the local noise-power spectrum: Theory and implementation in a framework for accelerated 3D image reconstruction with a morphological pyramid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Model-based iterative reconstruction (MBIR) offers improved noise-resolution tradeoffs and artifact reduction in conebeam CT compared to analytical reconstruction, but carries increased computational burden. An important consideration in minimizing computation time is reliable selection of the stopping criterion to perform the minimum number of iterations required to obtain the desired image quality. Most MBIR methods rely on a fixed number of iterations or relative metrics on image or cost-function evolution, and it would be desirable to use metrics that are more representative of the underlying image properties. A second front for reduction of computation time is the use of acceleration techniques (e.g. subsets or momentum). However, most of these techniques do not strictly guarantee convergence of the resulting MBIR method. A data-dependent analytical model of noise-power spectrum (NPS) for penalized weighted least squares (PWLS) reconstruction is proposed as an absolute metric of image properties for the fully converged volume. Distance to convergence is estimated as the root mean squared error (RMSE) between the estimated NPS and an NPS measured on a uniform region of interest (ROI) in the evolving volume. Iterations are stopped when the RMSE falls below a threshold directly related with the properties of the target image. Further acceleration was achieved by combining the spectral stopping criterion with a morphological pyramid (mPyr) in which the minimization of the PWLS cost-function is divided in a cascade of stages. The algorithm parameters (voxel size in this work) change between stages to achieve faster evolution in early stages, and a final stage with the target parameters to guarantee convergence. Transition between stages is governed by the spectral stopping criterion.

Original languageEnglish (US)
Title of host publication15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
EditorsSamuel Matej, Scott D. Metzler
PublisherSPIE
ISBN (Electronic)9781510628373
DOIs
StatePublished - Jan 1 2019
Event15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019 - Philadelphia, United States
Duration: Jun 2 2019Jun 6 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11072
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019
CountryUnited States
CityPhiladelphia
Period6/2/196/6/19

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Sisniega, A., Stayman, J. W., Capostagno, S., Weiss, C. R., Ehtiati, T., & Siewerdsen, J. H. (2019). Convergence criterion for MBIR based on the local noise-power spectrum: Theory and implementation in a framework for accelerated 3D image reconstruction with a morphological pyramid. In S. Matej, & S. D. Metzler (Eds.), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine [1107209] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072). SPIE. https://doi.org/10.1117/12.2534896